Ensemble model

[mw-boop]

Hi everyone,
I've got 10 yolo11 small segmentation models trained on the same dataset but with different hyperparameters. I've tried, and failed, to make an ensemble model using weight averaging. Is it possible to make an ensemble model with yolo11?
kind regards

[UltralyticsAssistant]

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[glenn-jocher]

Yes, you can create an ensemble model with YOLO11! Ultralytics provides an Ensemble class that allows combining multiple models. Here's how to use it with your 10 segmentation models:

from ultralytics.nn.tasks import Ensemble
from ultralytics import YOLO

# Load your 10 trained models
model_paths = ['model1.pt', 'model2.pt', 'model3.pt', ...]  # your 10 model paths
models = [YOLO(path) for path in model_paths]

# Create ensemble
ensemble = Ensemble()
for model in models:
    ensemble.append(model.model)

# Use the ensemble for inference
results = ensemble(image_tensor)

The ensemble concatenates predictions from all models and can provide better performance than individual models, especially when the models have different strengths from varied hyperparameters.